Spectral pre-processing for biomedical vibrational spectroscopy and microspectroscopic imaging

Chemometrics and Intelligent Laboratory Systems

Volumn 117, Issue , 2012, Pages 100-114

  Lasch, Peter ^a  

^a ROBERT KOCH INSTITUTE   (Germany)

Author keywords

Biomedical vibrational spectroscopy; Chemometrics; Hyperspectral imaging; Infrared spectroscopy; Raman spectroscopy; Spectral pre processing

Indexed keywords

ACCURACY; ARTICLE; BODY FLUID; CALIBRATION; CHEMOMETRICS; DATA ANALYSIS; DIGITAL FILTERING; EUKARYOTIC CELL; IMAGE QUALITY; MATHEMATICAL ANALYSIS; MEDICAL RESEARCH; MICROORGANISM; MICROSPECTROSCOPY; PRIORITY JOURNAL; QUALITY CONTROL; RAMAN SPECTROMETRY; REPRODUCIBILITY; SIGNAL NOISE RATIO; SPECTRAL PRE PROCESSING; SPECTROSCOPY; TISSUES; VIBRATIONAL SPECTROSCOPY; WATER VAPOR;

EID: 84867229920     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.03.011     Document Type: Article

References (115)

1. Heraud P., Wood B.R., Beardall J., McNaughton D. Effects of pre-processing of Raman spectra on in vivo classification of nutrient status of microalgal cells. Journal of Chemometrics 2006, 20:193-197.
2. Liu K.Z., Tsang K.S., Li C.K., Shaw R.A., Mantsch H.H. Infrared spectroscopic identification of beta-thalassemia. Clinical Chemistry 2003, 49:1125-1132.
3. Kohler A., Kristian A.N., Martens H. Chemometrics in Biospectroscopy. Handbook of Vibrational Spectroscopy 2006, PB - John Wiley & Sons, Ltd.
4. Saeys Y., Inza I., Larrañaga P. A review of feature selection techniques in bioinformatics. Bioinformatics 2007, 23:2507-2517.
5. Griffiths P.R., de Haseth J.A. Fourier Transform Infrared Spectroscopy 2007, John Wiley and Sons, New York. Second edition.
6. W. Herres, J. Gronholz, Understanding FT-IR data processing, Reprint Vols. 1(84), 3(85) Dr. Alfred Huethig Publishers (obtainable from Bruker Optics, Rheinstetten).
7. Naumann D. FT-IR spectroscopy of microorganisms at the Robert Koch Institute: experiences gained during a successful project. Biomedical Optical Spectroscopy, Proceedings of SPIE 2008, 68530F. A. Mahadevan-Jansen, W. Petrich, R.R. Alfano, A. Katz (Eds.).
8. Lasch P., Petrich W. Data acquisition and analysis in biomedical vibrational spectroscopy. RSC Analytical Spectroscopy Series 2011, 11:192-225. D. Moss (Ed.).
9. [March 1, 2012]. http://www.cytospec.com.
10. Dalby F.W., Nielsen H.H. Infrared spectrum of water vapor. Part I - the 6.26μm region. Journal of Chemical Physics 1956, 25:934-940.
11. Fabian H., Schultz C.P., Naumann D., Landt O., Hahn U., Saenger W. Secondary structure and temperature-induced unfolding and refolding of ribonuclease T1 in aqueous solution. A Fourier transform infrared spectroscopic study. Journal of Molecular Biology 1993, 232:967-981.
12. Fabian H., Schultz C.P. Fourier transform infrared spectroscopy in peptide and protein analysis. Encyclopedia of Analytical Chemistry 2000, 5779-5803. John Wiley & Sons Ltd, Chichester. R.A. Meyers (Ed.).
13. Lasch P., Schultz C.P., Naumann D. The thermotropic and ionotropic phase behaviour of mixed vesicles made up from lipopolysaccharides, 1,2-dimyristoylphosphatidylethanolamine-d54, and OmpF from Escherichia coli. FT-IR-spectroscopic investigations. Biophysical Journal 1998, 75:840-852.
14. Lasch P., Petras T., Ullrich O., Backmann J., Naumann D., Grune T. Hydrogen peroxide induced damage of RNase A is followed by degradation by proteasome and FT-IR spectroscopy. Journal of Biological Chemistry 2001, 276:9492-9502.
15. Lasch P., Chiriboga L., Yee H., Diem M. Infrared spectroscopy of human cells and tissue: detection of disease. Technology in Cancer Research & Treatment 2002, 1:1-5.
16. Lasch P., Diem M., Hänsch W., Naumann D. Artificial neural networks as supervised techniques for FT-IR microspectroscopic imaging. Journal of Chemometrics 2006, 20:209-220.
17. Randolph T.W. Scale-based normalization of spectral data. Cancer Biomarkers 2006, 2:135-144.
18. Geladi P., MacDougall D., Martens H. Linearization and scatter-correction for near-infrared reflectance spectra of meat. Applied Spectroscopy 1985, 39:377-562.
19. Martens H., Nielsen J.P., Engelsen S.B. Light scattering and light absorbance separated by extended multiplicative signal correction. Application to near-infrared transmission analysis of powder mixtures. Analytical Chemistry 2003, 75:394-404.
20. Barnes R.J., Dhanoa M.S., Lister S.J. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra. Applied Spectroscopy 1989, 43:772-777.
21. Mazet V., Carteret C., Brie D., Idier J., Humbert B. Background removal from spectra by designing and minimising a non-quadratic cost function. Chemometrics and Intelligent Laboratory Systems 2005, 76:121-133.
22. Mie G. Contribution to the optical properties of turbid media, in particular of colloidal suspensions of metals. Annals of Physics (Leipzig) 1908, 25:377-452.
23. Mohlenhoff B., Romeo M., Diem M., Wood B.R. Mie-type scattering and non-Beer-Lambert absorption behavior of human cells in infrared microspectroscopy. Biophysical Journal 2005, 88:3635-3640.
24. Savitzky A., Golay M. Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry 1964, 36:1627.
25. Schulze G., Jirasek A., Yu M.M., Lim A., Turner R.F., Blades M.W. Investigation of selected baseline removal techniques as candidates for automated implementation. Applied Spectroscopy 2005, 59:545-574.
26. Marchand P., Marmet L. Binomial smoothing filter: a way to avoid some pitfalls of least square polynomial smoothing. The Review of Scientific Instruments 1983, 54:1034-1041.
27. Holler F., Burns D.H., Callis J.B. Direct use of second derivatives in curve-fitting procedures. Applied Spectroscopy 1989, 43:877-882.
28. Steinier J., Termonia Y., Deltour J. Smoothing and differentiation of data by simplified least square procedure. Analytical Chemistry 1972, 44:1906-1909.
29. [November 1, 2011]. http://en.wikipedia.org/wiki/Savitzky-Golay_smoothing_filter.
30. Stone H. Mathematical resolution of overlapping bands. Journal of the Optical Society of America 1962, 52:998-1003.
31. Kauppinen J.K., Moffat D.J., Mantsch H.H., Cameron D.G. Fourier self-deconvolution: a method for resolving intrinsically overlapped bands. Applied Spectroscopy 1981, 35:271-276.
32. Kauppinen J.K., Moffat D.J., Mantsch H.H., Cameron D.G. Self-deconvolution and first order derivatives using Fourier transforms. Analytical Chemistry 1981, 53:1454-1457.
33. Kauppinen J.K., Moffat D.J., Mantsch H.H., Cameron D.G. Noise in Fourier self-deconvolution. Applied Optics 1981, 20:1866.
34. Moffat D.J., Kauppinen J.K., Mantsch H.H. Computers and infrared spectroscopy: evolution and revolution. Canadian Journal of Chemistry 1991, 69:1781-1785.
35. Yang W.J., Griffiths P.R., Byler M., Susi H. Protein conformation by infrared spectroscopy: resolution enhancement by Fourier self-deconvolution. Applied Spectroscopy 1985, 39:281-28.
36. Surewicz W.K., Mantsch H.H., Chapman D. Determination of protein secondary structure by Fourier transform infrared spectroscopy: a critical assessment. Biochemistry 1993, 32:389-394.
37. Barth A., Zscherp C. What vibrations tell us about proteins. Quarterly Reviews of Biophysics 2002, 35:369-430.
38. Lórenz-Fonfría V.A., Padrós E. The role and selection of the filter function in Fourier self-deconvolution revisited. Applied Spectroscopy 2009, 63:791-799.
39. Smeller L., Goossens K., Heremans K. How to minimize certain artifacts in Fourier self-deconvolution. Applied Spectroscopy 1995, 49:1538-1542.
40. Bassan P., Byrne H.J., Lee J., Bonnier F., Clarke C., Dumas P., Gazi E., Gardner P. Reflection contributions to the dispersion artefact in FTIR spectra of single biological cells. Analyst 2009, 134:1171-1175.
41. Bassan P., Byrne H.J., Bonnier F., Lee J., Dumas P., Gardner P. Resonant Mie scattering in infrared spectroscopy of biological materials - understanding the 'dispersion artefact'. Analyst 2009, 134:1586-1593.
42. Bassan P., Kohler A., Martens H., Lee J., Byrne H.J., Dumas P., Gazi E., Gardner P. Resonant Mie Scattering (RMieS) correction of infrared spectra from highly scattering biological samples. Analyst 2010, 135:268-277.
43. Bassan P., Kohler A., Martens H., Lee J., Jackson E., Lockyer N., Dumas P., Gardner P. RMieS-EMSC correction for infrared spectra of biological cells: extension using full Mie theory and GPU computing. Journal of Biophotonics 2010, 3:609-620.
44. Max J.J., Chapados C. Isotope effects in liquid water by infrared spectroscopy. Journal of Chemical Physics 2002, 116:4626-4642.
45. Zhang Z.D., Ben-Amotz D. Removal of cosmic spikes from hyper-spectral images using a hybrid upper-bound spectrum method. Applied Spectroscopy 2002, 56:91-98.
46. do Lago C.L., Juliano V.F., Kascheres C. Applying moving median digital filter to mass spectrometry and potentiometric titration. Analytica Chimica Acta 1995, 310:281-288.
47. Zhao J. Image curvature correction and cosmic removal for high-throughput dispersive Raman spectroscopy. Applied Spectroscopy 2003, 57:1368-1375.
48. Phillips G.R., Harris J.M. Polynomial filters for data sets with outlying or missing observations: application to charge-coupled-device-detected Raman spectra contaminated by cosmic rays. Analytical Chemistry 1990, 62:2351-2357.
49. Li S., Dai L. An improved algorithm to remove cosmic spikes in Raman spectra for online monitoring. Applied Spectroscopy 2011, 65:1300-1306.
50. Hill W., Rogalla D. Spike-correction of weak signals from charge-coupled devices and its application to Raman spectroscopy. Analytical Chemistry 1992, 64:2575-2579.
51. De Luca A.C., Mazilu M., Riches A., Herrington C.S., Dholakia K. Online fluorescence suppression in modulated Raman spectroscopy. Analytical Chemistry 2010, 82:738-745.
52. Mosier-Boss P.A., Lieberman S.H., Newbery R. Fluorescence rejection in Raman spectroscopy by shifted-spectra, edge detection, and FFT filtering techniques. Applied Spectroscopy 1995, 49:630-638.
53. Kamogawa K., Fujii T., Kitagawa T. Improved fluorescence rejection in measurements of Raman spectra of fluorescent compounds. Applied Spectroscopy 1988, 42:248-254.
54. Rohleder D., Kiefer W., Petrich W. Quantitative analysis of serum and serum ultrafiltrate by means of Raman spectroscopy. Analyst 2004, 129:906-911.
55. Williams K.P.J., Gerrard D.L. The use of 752.5 and 799.3nm laser excitation in Raman spectroscopy. Optics and Laser Technology 1985, 17:245-248.
56. Fodor S.P.A., Spiro T.G. Ultraviolet resonance Raman spectroscopy of DNA with 200-266-nm laser excitation. Journal of the American Chemical Society 1986, 108:3198-3205.
57. Van Duyne R.P., Jeanmaire D.L., Shriver D.F. Mode-locked laser Raman spectroscopy - a new technique for the rejection of interfering background luminescence signals. Analytical Chemistry 1974, 46:213-222.
58. Morris M.D., Matousek P., Towrie M., Parker A.W., Goodship A.E., Draper E.R. Kerr-gated time-resolved Raman spectroscopy of equine cortical bone tissue. Journal of Biomedical Optics 2005, 10:14014.
59. Bowley H.J., Gerrard D.L. The use of diode array detectors in conjunction with continuous wave gas lasers for anti-Stokes Raman spectroscopy. Optics and Laser Technology 1986, 18:33-35.
60. Angel S.M., DeArmond M.K., Hanck K.W., Wertz D.W. Computer-controlled instrument for the recovery of a resonance Raman spectrum in the presence of strong luminescence. Analytical Chemistry 1984, 56:3000-3001.
61. Shreve A.P., Cherepy N.J., Mathies R.A. Effective rejection of fluorescence interference in Raman spectroscopy using a shifted excitation difference technique. Applied Spectroscopy 1992, 46:707-711.
62. Zhao J., Carrabba M.M., Allen F.S. Automated fluorescence rejection using shifted excitation Raman difference spectroscopy. Applied Spectroscopy 2002, 56:834-845.
63. Mahadevan-Jansen A., Richards-Kortum R.R. Raman spectroscopy for the detection of cancers and precancers. Journal of Biomedical Optics 1996, 1:31-70.
64. Lieber C.A., Mahadevan-Jansen A. Automated method for subtraction of fluorescence from biological Raman spectra. Applied Spectroscopy 2003, 57:1363-1367.
65. Zhao J., Lui H., McLean D.I., Zeng H. Automated autofluorescence background subtraction algorithm for biomedical Raman spectroscopy. Applied Spectroscopy 2007, 61:1225-1232.
66. Zhang D., Ben-Amotz D. Enhanced chemical classification of Raman images in the presence of strong fluorescence interference. Applied Spectroscopy 2000, 54:1379-1383.
67. Hasegawa T., Nishijo J., Umemura J. Separation of Raman spectra from fluorescence emission background by principal component analysis. Chemical Physics Letters 2000, 317:642-646.
68. Hua Y., Jiang T., Shen A., Lib W., Wanga X., Hub J. A background elimination method based on wavelet transform for Raman spectra. Chemometrics and Intelligent Laboratory Systems 2007, 85:94-101.
69. Zhang Z.M., Chen S., Liang Y.Z., Liu Z.X., Zhang Q.M., Ding L.X., Ye F., Zhou H. An intelligent background-correction algorithm for highly fluorescent samples in Raman spectroscopy. Journal of Raman Specroscopy 2009, 41:659-669.
70. Mallat S.G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 1989, 11:674-693.
71. Graps A. An introduction to wavelets. IEEE Computational Science and Engineering 1995, 2:50-61.
72. Mallet Y., Coomans D., De Vel O. Recent developments in discriminant analysis on high dimensional spectral data. Chemometrics and Intelligent Laboratory Systems 1996, 35:157-173.
73. Alsberg B.K., Woodward A.M., Kell D.B. An introduction to wavelet transforms for chemometricians: a time-frequency approach. Chemometrics and Intelligent Laboratory Systems 1997, 37:215-239.
74. Walczak B., Massart D.L. Noise suppression and signal compression using the wavelet packet transform. Chemometrics and Intelligent Laboratory Systems 1997, 36:81-94.
75. Walczak B., Bogaert B., Massart D.L. Application of wavelet packet transform in pattern recognition of near-IR data. Analytical Chemistry 1996, 68:1742-1747.
76. Gobinet C., Vrabie V., Manfait M., Piot O. Preprocessing methods of Raman spectra for source extraction on biomedical samples: application on paraffin-embedded skin biopsies. IEEE Transactions on Biomedical Engineering 2009, 56:1371-1382.
77. Wollman S.T., Bohn P.W. Evaluation of polynomial fitting functions for use with CCD arrays in Raman spectroscopy. Applied Spectroscopy 1993, 47:125-126.
78. Simpson J.V., Oshokoya O., Wagner N., Liu J., Jiji R.D. Pre-processing of ultraviolet resonance Raman spectra. Analyst 2011, 136:1239-1247.
79. Hopkinson G.R., Goodman T.M., Prince S.R. A guide to the use and calibration of detector array equipment. SPIE - The International Society for Optical Engineering, Bellingham, Washington 2004.
80. Automated wavelength & intensity calibration routines significantly improves accuracy of recorded spectra, Princeton Instruments Spectroscopy Group. Technical Note 2011.
81. Tseng C.H., Ford J.F., Mann C.K., Vickers T.J. Wavelength calibration of a multichannel spectrometer. Applied Spectroscopy 1993, 47:1808-1813.
82. [November 1, 2011]. http://www.astm.org.
83. Carter D.A., Thompson W.R., Wade R., Chad E.T., Pemberton J.E. Frequency/wavelength calibration of multipurpose multichannel Raman spectrometers. Part II: calibration fit considerations and calibration standards. Applied Spectroscopy 1995, 49:1561-1576.
84. Nielsen N.P.V., Carstensen J.M., Smedsgaard J. Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimised warping. Journal of Chromatography. A 1998, 805:17-35.
85. Tomasi G., van den Berg F., Andersson C. Correlation optimized warping and dynamic time warping as preprocessing methods for chromatographic data. Journal of Chemometrics 2004, 18:231-241.
86. Haq I., Chowdhry B.Z., Chaires J.B. Singular value decomposition of 3-D DNA melting curves reveals complexity in the melting process. European Biophysics Journal 1997, 26:419-426.
87. van Manen H.J., Kraan M., Roos Y.D., Otto C. Intracellular chemical imaging of heme-containing enzymes involved in innate immunity using resonance Raman microscopy. The Journal of Physical Chemistry. B 2004, 48:18762-18771.
88. Turner D.D., Knuteson R.O., Revercomb H.E., Lo C., Dedecker R.G. Noise reduction of atmospheric emitted radiance interferometer (AERI) observations using principal component analysis. Journal of Atmospheric and Oceanic Technology 2006, 23:1223-1238.
89. Green A.A., Berman M., Switzer P., Craig M.D. A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Transactions on Geoscience and Remote Sensing 1988, 26:65-74.
90. A.A. Nielsen, Analysis of Regularly and Irregularly Sampled Spatial, Multivariate, and Multi-temporal Data, Dissertation, IMM/Technical University of Denmark, Lyngby 1994.
91. Kruse F.A., Boardman J.W., Lefkoff A.B. Extraction of compositional information for trafficability mapping from hyperspectral data. Proceedings of SPIE 2000, 4049:262.
92. Bhargava R., Wang S.Q., Koenig J.L. Route to higher fidelity FT-IR imaging. Applied Spectroscopy 2000, 54:486-495.
93. Reddy R.K., Bhargava R. Accurate histopathology from low signal-to-noise ratio spectroscopic imaging data. Analyst 2010, 135:2818-2825.
94. Boardman J.W., Kruse F.A. Automated spectral analysis: a geologic example using AVIRIS data, north Grapevine Mountains, Nevada. Proceedings of the Tenth Thematic Conference on Geologic Remote Sensing, Environmental Research Institute of Michigan, Ann Arbor, MI 1994, vol. 1:407-418.
95. Cai T.T., Zhang D., Ben-Amotz D. Enhanced chemical classification of raman images using multiresolution wavelet transformation. Applied Spectroscopy 2001, 55:1124-1130.
96. Wang Y.P., Wang Y., Spencer P. Fuzzy clustering of Raman spectral imaging data with a wavelet-based noise-reduction approach. Applied Spectroscopy 2006, 60:826-832.
97. [March 1, 2012]. http://www.andor.com.
98. Lasch P., Haensch W., Naumann D., Diem M. Imaging of colorectal adenocarcinoma using FT-IR microspectroscopy and cluster analysis. Biochimica et Biophysica Acta 2004, 1688:176-186.
99. Lasch P., Naumann D. Spatial resolution in infrared microspectroscopic imaging of tissues. Biochimica et Biophysica Acta 2006, 1758:814-829.
100. Behrend C.J., Tarnowski C.P., Morris M.D. Identification of outliers in hyperspectral raman image data by nearest neighbor comparison. Applied Spectroscopy 2002, 56:1458-1461.
101. Nyquist H. Certain topics in telegraph transmission theory. AIEE Transactions 1928, 47:617-644.
102. Nasse M.J., Walsh M.J., Mattson E.C., Reininger R., Kajdacsy-Balla A., Macias V., Bhargava R., Hirschmugl C.J. High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams. Nature Methods 2011, 8:413-416.
103. Carr G.L. Resolution limits for infrared microspectroscopy explored with synchrotron radiation. The Review of Scientific Instruments 2001, 72:1613-1619.
104. Schuster K.C., Reese I., Urlaub E., Gapes J.R., Lendl B. Multidimensional information on the chemical composition of single bacterial cells by confocal Raman microspectroscopy. Analytical Chemistry 2000, 72:5529-5534.
105. Rösch P., Harz M., Schmitt M., Peschke K.D., Ronneberger O., Burkhardt H., Motzkus H.W., Lankers M., Hofer S., Thiele H., Popp J. Chemotaxonomic identification of single bacteria by micro-Raman spectroscopy: application to clean-room-relevant biological contaminations. Applied and Environmental Microbiology 2005, 71:1626-1637.
106. Hermelink A., Brauer A., Lasch P., Naumann D. Imaging phenotypic heterogeneity within microbial populations at the single cell level by confocal Raman microspectroscopy. Analyst 2009, 134:1149-1153.
107. Lasch P., Hermelink A., Naumann D. Correction of axial chromatic aberrations in confocal Raman microspectroscopic measurements of a single microbial spore. Analyst 2009, 134:1162-1170.
108. Lasch P., Schmitt J., Beekes M., Udelhoven T., Eiden M., Fabian H., Petrich W., Naumann D. Antemortem identification of bovine spongiform encephalopathy from serum using infrared spectroscopy. Analytical Chemistry 2003, 75:6673-6678.
109. Xu L., Zhou Y.P., Tang L.J., Wu H.L., Jiang J.H., Shen G.L., Yu R.Q. Ensemble preprocessing of near-infrared (NIR) spectra for multivariate calibration. Analytica Chimica Acta 2008, 616:138-143.
110. Delwiche S.R. J.B. 3rd. Reeves, A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression. Applied Spectroscopy 2010, 64:73-82.
111. Delwiche S.R., Graybosch R.A. Examination of spectral pretreatments for partial least-squares calibrations for chemical and physical properties of wheat. Applied Spectroscopy 2003, 57:1517-1527.
112. Candolfi A., De Maesschalc R., Jouan-Rimbaud D., Hailey P.A., Massart D.L. The influence of data pre-processing in the pattern recognition of excipients near-infrared spectra. Journal of Pharmaceutical and Biomedical Analysis 1999, 21:115-132.
113. Afseth N.K., Segtnan V.H., Wold J.P. Raman spectra of biological samples: a study of preprocessing methods. Applied Spectroscopy 2006, 60:1358-1367.
114. Helm D., Labischinski H., Schallehn G., Naumann D. Classification and identification of bacteria by Fourier-transform infrared spectroscopy. Journal of General Microbiology 1991, 137:69-79.
115. Udelhoven T., Novozhilov M., Schmitt J. The NeuroDeveloper(R): a tool for modular neural classification of spectroscopic data. Chemometrics and Intelligent Laboratory Systems 2003, 66:219-226.